Implementation of the Maximum Bandwidth Ratio of Satellite Radio Communication Systems under the Conditions for Intramodal Dispersion of Transionospheric Radio Channels

The problem of significant extension of the band of the transionospheric radio channel to the maximum possible values is solved to improve the efficiency of satellite communication systems. Hardware and software are created to suppress the group delay dispersion using methods of data mining for expe...

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Bibliographic Details
Published in:Journal of communications technology & electronics 2023-06, Vol.68 (6), p.666-673
Main Authors: Ivanov, D. V., Ivanov, V. A., Ryabova, N. V., Kislitsyn, A. A.
Format: Article
Language:English
Subjects:
Adaptation
Algorithms
Bandwidths
Big Data
Channels
Communications Engineering
Communications systems
Data mining
Data processing
Dispersion
Engineering
Frequency response
Group delay
Machine learning
Networks
On the 85th Anniversary of Dmitrii Sergeevich Lukin
Radio communications
Satellite communications
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Summary:The problem of significant extension of the band of the transionospheric radio channel to the maximum possible values is solved to improve the efficiency of satellite communication systems. Hardware and software are created to suppress the group delay dispersion using methods of data mining for experimental diagnostics of a transionospheric communication line. Algorithms and tools for intelligent sensory diagnostics of wideband radio channels with adaptation to dispersion variability are developed. In the absence of adaptation, it is possible to create radio channels of undistorted transmission with a bandwidth ratio of no greater than 4.5%, while adaptation to dispersion variability makes it possible to increase the bandwidth ratio to 11.5%. The greatest bandwidth ratio (20–25%) for dispersion-free transmission can be achieved with the aid of adaptive inverse filtering of the channel frequency response in combination with such intelligent methods as equalization with error, machine learning of channel equalizer, and big data processing.
ISSN:1064-2269
1555-6557
DOI:10.1134/S1064226923060049